(January 25, 2011) represented a real opportunity to bring about fundamental changes in Egyptian foreign policy and to start a new phase that would cut off all the negative and problematic aspects of Egyptian politics in the period before the revolution. Through the employment of Egypt's huge balance and the role of historical is a civilization rooted in the roots of thousands of years and Islamic reference represented over more than a thousand years the Islamic medium of religion in the start of vision and tools to achieve the Egyptian national interest, and safeguarding Egyptian national security in its comprehensive sense. The research attempts to answer a central question: Is there a role for Egyptian soft power in the Islamic world in general and in the Mediterranean region in particular? In the answer to the above question, the research will provide a basic hypothesis: "Egyptian soft power has a role and influence in the Islamic world in general and in the Middle East in particular, but the effectiveness of this role and influence varied according to the different tools and times, and the reflection on the ground." The research is based on several approaches to achieve the desired results. The analytical approach to the contents of the Egyptian discourse will be relied upon, which helped to gain insight into the nature of Egyptian foreign policy and its position on the use of soft power. And adopted a comparative approach to demonstrate Egypt's use of solid power and its use of soft power in the Middle East region. Keywords: employment strategy, soft power, January 25 events in Egypt, techno-information revolution, diplomacy, Egyptian foreign policy.
Correct grading of apple slices can help ensure quality and improve the marketability of the final product, which can impact the overall development of the apple slice industry post-harvest. The study intends to employ the convolutional neural network (CNN) architectures of ResNet-18 and DenseNet-201 and classical machine learning (ML) classifiers such as Wide Neural Networks (WNN), Naïve Bayes (NB), and two kernels of support vector machines (SVM) to classify apple slices into different hardness classes based on their RGB values. Our research data showed that the DenseNet-201 features classified by the SVM-Cubic kernel had the highest accuracy and lowest standard deviation (SD) among all the methods we tested, at 89.51 % 1.66 %. This
... Show MoreDue to the importance of the extraction process in many engineering and medical industries, in addition to great interest in medicinal plants, in this research, microwave-assisted extraction has been applied to extract some active compounds from Rosmarinus officinalis leaves. The optimal extraction conditions were then determined by calculating the ratio and extraction efficiency. The process has also been described through kinetic study by applying five kinetic models, the Hyperbolic diffusion model, Power low model, the First order reaction model, Elovich's model, and Fick's second law diffusion model and determining their compatibility with the studies operation, and determining the kinetic constants for each model. The result
... Show MoreGelatin-grafted N- proflavine acryl amide was synthesized through two steps; firstly the Gelatin was grafted with acrylic acid free radically using Ammonium per-sulfate at 60℃, Then it was modified to its corresponding acyl chloride derivation, second step included the substitution with amino group of proflavine, in this research Gelatin was used as a natural nontoxic, water soluble polymer as a drug carrier. The prepared pro drug polymer was characterized by FTIR and 1H-NMR spectroscopies, Controlled drug release was studied in different pH values at 37℃. Many advantages were obtained comparing with other known methods.
KE Sharquie, AA Noaimi, AG Al-Ghazzi, Journal of Dermatology & Dermatologic Surgery, 2015 - Cited by 19
Increasing demands on producing environmentally friendly products are becoming a driving force for designing highly active catalysts. Thus, surfaces that efficiently catalyse the nitrogen reduction reactions are greatly sought in moderating air-pollutant emissions. This contribution aims to computationally investigate the hydrodenitrogenation (HDN) networks of pyridine over the γ-Mo2N(111) surface using a density functional theory (DFT) approach. Various adsorption configurations have been considered for the molecularly adsorbed pyridine. Findings indicate that pyridine can be adsorbed via side-on and end-on modes in six geometries in which one adsorption site is revealed to have the lowest adsorption energy (–45.3 kcal/mol). Over a nitr
... Show More<p>Currently, breast cancer is one of the most common cancers and a main reason of women death worldwide particularly in<strong> </strong>developing countries such as Iraq. our work aims to predict the type of tumor whether benign or malignant through models that were built using logistic regression and neural networks and we hope it will help doctors in detecting the type of breast tumor. Four models were set using binary logistic regression and two different types of artificial neural networks namely multilayer perceptron MLP and radial basis function RBF. Evaluation of validated and trained models was done using several performance metrics like accuracy, sensitivity, specificity, and AUC (area under receiver ope
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